OBO Foundry dashboard analysis

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/tmp/ipykernel_535/4293058459.py:21: FutureWarning:

The `inplace` parameter in pandas.Categorical.reorder_categories is deprecated and will be removed in a future version. Reordering categories will always return a new Categorical object.

Ontologies by number of axioms

Ontologies by number of classes

Ontologies by how many ontologies use it

Different serialisations used

RDF/XML Syntax    4
unknown           1
Name: syntax, dtype: int64

Breakdown of used Axiom Types

	count	mean	std	min	25%	50%	75%	max
AnnotationAssertion	4	79031.4	165919.598057	0.0	2.0	8675.0	10773.0	375707.0
Declaration	4	7956.8	13726.474445	0.0	2.0	1989.0	5628.0	32165.0
EquivalentClasses	4	2239.0	3305.080937	0.0	1.0	584.0	2842.0	7768.0
SubAnnotationPropertyOf	2	7.8	16.887865	0.0	0.0	0.0	1.0	38.0
SubClassOf	2	9570.4	20753.845024	0.0	0.0	0.0	1167.0	46685.0
DisjointClasses	1	15.6	34.882660	0.0	0.0	0.0	0.0	78.0
SubObjectPropertyOf	1	0.8	1.788854	0.0	0.0	0.0	0.0	4.0
SubPropertyChainOf	1	1.4	3.130495	0.0	0.0	0.0	0.0	7.0
SymmetricObjectProperty	1	0.2	0.447214	0.0	0.0	0.0	0.0	1.0

Breakdown of used OWL Class Expression constructs

	count	mean	std	min	25%	50%	75%	max
Class	4	34023.4	64761.813647	0.0	3.0	6184.0	14550.0	149380.0
ObjectSomeValuesFrom	4	4614.4	7965.189627	0.0	1.0	1151.0	3257.0	18663.0
ObjectIntersectionOf	3	2279.4	3287.162880	0.0	0.0	717.0	2926.0	7754.0
ObjectUnionOf	1	2.8	6.260990	0.0	0.0	0.0	0.0	14.0

OBO Score (Experimental)

	ontology	score	score_dash	score_impact
2	maxo	0.564	0.727	0.4
0	ecto	0.522	0.844	0.2
3	mondo	0.474	0.949	0.0
4	tmp	0.141	0.282	0.0
1	hpo	0.000	0.000	0.0

OBO Score Summary

	count	mean	std	min	25%	50%	75%	max
score	5.0	0.3402	0.253208	0.0	0.141	0.474	0.522	0.564
score_dash	5.0	0.5604	0.403345	0.0	0.282	0.727	0.844	0.949
score_impact	5.0	0.1200	0.178885	0.0	0.000	0.000	0.200	0.400

OBO dependency graph